基于颗粒应力的深层超压预测方法研究:以准噶尔盆地腹部地区为例

异常地层压力预测是油气勘探和钻井工程关注的热点问题。对于勘探程度低、探井稀少的地区,压力分布特征的不明确制约油气勘探进展和钻井高效实施,因此,地层压力预测精度有待提高。在地层孔隙静力平衡原理的指导下,以准噶尔盆地腹部实际地质资料和压力测试数据为基础,建立了基于颗粒应力的地层压力预测模型。研究表明,(1)经典压力预测模型存在缺陷,特察模型并非静力平衡方程,有效应力不是骨架真正承担的力;(2)采用孔隙型介质颗粒应力参数建立了孔隙静力平衡方程,通过研究区深层侏罗系已钻井超压预测对比,发现基于颗粒应力的压力预测方法精度有所提高;(3)压力预测模型仅考虑了内动力因素即沉积增压,超压成因补偿不可忽视。研究区发现准南构造挤压应力向盆地内部传递,形成了规律性分布的超压分量,附加地应力的补偿是提高超压预测精度的有效途径。

Distribution Prediction of High Overpressure in Jurassic Moxizhuang-Yongjin Area,Central Junggar Basin

Prediction of abnormal formation pressure is a hot issue in oil and gas exploration and drilling engineering. For the areas with low exploration degree and few exploration wells, the unclear pore pressure distribution characteristics would hamper oil and gas exploration and efficient drilling execution. Therefore, the prediction accuracy of pore pressure needs to be improved. In this study, based on the static equilibrium principle of formation pores, a new pore pressure prediction model based on grain stress is established according to the actual geological data and pressure test data of Yong-Mo area in the central Junggar Basin. The results show that: (1) the classical pressure prediction model has defects. The Terzaghi model is not in static equilibrium, and effective stress is not the actual support force of grains, but a man-made physical variable; (2) we established the pore static equilibrium equation by using the grain stress parameters of porous medium. By comparing the prediction of overpressure of drilling wells in the local deep Jurassic sequences, we found that the pressure prediction accuracy based on grain stress is improved; (3) The pressure prediction model only considers the internal dynamic factor (i.e.deposition supercharging), and overpressure origin compensation cannot be ignored. We found that the local tectonic compression in the southern basinal margin has transferred to the basin interior, and formed the overpressure component with regular distribution. The compensation of additional tectonic stress is an effective way to improve the overpressure prediction accuracy.